Common Analytics Interview Questions

You are excited. You have got that much awaited interview call for that dream analytics job. You are confident you will be perfect for the job. Now all that remains is convincing the interviewer. Don’t you wish you knew what kind of questions they are going to be ask?

As co founder and one of the chief trainers at Jigsaw Academy, an online analytics training institute, I regularly get calls from our students days before their scheduled interview asking me just this. I am going to share with you just what I share with them. Here you go. Below are a few of the more popular questions you could get asked and the corresponding answers in a nutshell.

Question 1. Can you outline the various steps in an analytics project?

Broadly speaking these are the steps. Of course these may vary slightly depending

on the type of problem, data, tools available etc.

1.  Problem definition  – The first step is to of course understand the business

problem. What is the problem you are trying to solve – what is the business context?

Very often however your client may also just give you a whole lot of data and ask

you to do something with it. In such a case you would need to take a more

exploratory look at the data. Nevertheless if the client has a specific problem that

needs to be tackled, then then first step is to clearly define and understand the

problem. You will then need to convert the business problem into an analytics

problem. I other words you need to understand exactly what you are going to predict

with the model you build. There is no point in building a fabulous model, only to

realise later that what it is predicting is not exactly what the business needs.

2.  Data Exploration  – Once you have the problem defined, the next step is to

explore the data and become more familiar with it. This is especially important when

dealing with a completely new data set.

3.  Data Preparation  – Now that you have a good understanding of the data, you will

need to prepare it for modelling. You will identify and treat missing values, detect

outliers, transform variables, create binary variables if required and so on. This

stage is very influenced by the modelling technique you will use at the next stage.

For example, regression involves a fair amount of data preparation, but decision

trees may need less prep whereas clustering requires a whole different kind of prep

as compared to other techniques.

4.  Modelling  – Once the data is prepared, you can begin modelling. This is usually

an iterative process where you run a model, evaluate the results, tweak your

approach, run another model, evaluate the results, re-tweak and so on….. You go

on doing this until you come up with a model you are satisfied with or what you feel

is the best possible result with the given data.

5. Validation   – The final model (or maybe the best 2-3 models) should then be put

through the validation process. In this process, you test the model using completely

new data set i.e. data that was not used to build the model. This process ensures

that your model is a good model in general and not just a very good model for the

specific data earlier used (Technically, this is called avoiding over fitting)

6. Implementation and tracking – The final model is chosen after the validation.

Then you start implementing the model and tracking the results. You need to track

results to see the performance of the model over time. In general, the accuracy of a

model goes down over time. How much time will really depend on the variables –

how dynamic or static they are, and the general environment – how static or

dynamic that is.

 

Question 2.   What do you do in data exploration?

Data exploration is done to become familiar with the data. This step is especially

important when dealing with new data. There are a number of things you will want to

do in this step –

a.        What is there in the data – look at the list of all the variables in the data set.

Understand the meaning of each variable using the data dictionary. Go back to the

business for more information in case of any confusion.

b.        How much data is there – look at the volume of the data (how many

records), look at the time frame of the data (last 3 months, last 6 months etc.)

c.         Quality of the data – how much missing information, quality of data in each

variable. Are all fields usable? If a field has data for only 10% of the observations,

then maybe that field is not usable etc.

d.        You will also identify some important variables and may do a deeper

investigation of these. Like looking at averages, min and max values, maybe

10th and 90th percentile as well…

e.        You may also identify fields that you need to transform in the data prep stage.

 

Question 3: What do you do in data preparation?

In data preparation, you will prepare the data for the next stage i.e. the modelling

stage. What you do here is influenced by the choice of technique you use in the next

stage.

But some things are done in most cases – example identifying missing values and

treating them, identifying outlier values (unusual values) and treating them,

transforming variables, creating binary variables if required etc,

This is the stage where you will partition the data as well. i.e create training data (to

do modelling) and validation (to do validation).

 

Question 4: How will you treat missing values?

The first step is to identify variables with missing values. Assess the extent of

missing values. Is there a pattern in missing values? If yes, try and identify the

pattern. It may lead to interesting insights.

If no pattern, then we can either ignore missing values (SAS will not use any

observation with missing data) or impute the missing values.

Simple imputation – substitute with mean or median values

OR

Case wise imputation –for example, if we have missing values in the income field.

 

Question 5: How will you treat outlier values?

You can identify outliers using graphical analysis and univariate analysis. If there are

only a few outliers, you can assess them individually. If there are many, you may

want to substitute the outlier values with the 1stpercentile or the 99th percentile

values.

If there is a lot of data, you may decide to ignore records with outliers.

Not all extreme values are outliers. Not all outliers are extreme values.

 

Question 6: How do you assess the results of a logistic regression analysis?

You can use different methods to assess how good a logistic model is.

a. Concordance – This tells you about the ability of the model to discriminate

between the event happening and not happening.

b. Lift – It helps you assess how much better the model is compared to random

selection.

c. Classification matrix – helps you look at the false positives and true negatives.

Some other general questions you will most likely be asked:

What have you done to improve your data analytics knowledge in the past year?

What are your career goals?

Why do you want a career in data analytics?

The answers to these questions will have to be unique to the person answering it.

The key is to show confidence and give well thought out answers that demonstrate

you are knowledgeable about the industry and have the conviction to work hard and

excel as a data analyst.

The questions we’re looking at in this article are:

What diagrams and other methods do you use to capture business

requirements?

What experience do you have with agile methodologies?

How many business cases have you worked on? How were you involved?

Tell me about a time you have had trouble working with a stakeholder

Tell me about a time you had conflicting requirements from different

stakeholders

What is the most important skill of a business analyst, in your opinion?

Can you briefly explain what a use case diagram is?

Can you explain what alternative and exception flows are in a use case

description?

What is the difference between a use case and a test case?

 

What diagrams and other methods do you use to capture business requirements?

Business analysts use different methods of gathering requirements and information from

people they deal with. This question is designed to make you think about the tools that you

use, and how you can adapt to the different needs of documenting requirements.

You should have a couple of answers here, and mention how flexibility

is important. Flow charts are often helpful to determine processes. You can also specify

any UML diagrams that you use in your process, such as activity or sequence diagrams.

As far as methods go, briefly describe how you get requirements from people. This can be

in small workshops, or sitting one on one with someone. It can also help to let a user show

you a problem or a process themselves, with you observing. The idea here, once again, is

to show that you’re flexible with the tools and methods you use.

 

What experience do you have with agile methodologies?This question is just a question on experience. Agile methodologies are gaining popularity in

software projects for many reasons, and employers are constantly looking for IT

professionals that have those skills. It’s important not to lie on this question,

but also to show your enthusiasm.

If you have experience, that’s great. Mention what roles you’ve been involved in, what work

was performed, and how the team worked together. Mention time periods that you have

worked with Agile, such as “I spent six months on a software project that was running Agile

development”. Remain positive about the Agile methodology and experience.

If you don’t have experience, which many of you won’t, then it’s still OK. Don’t lie and say

that you have experience, because you’ll get caught out eventually and it won’t be good.

The employer is asking because they are probably looking for people with an interest in

Agile. You can mention an interest you have, or that you’d like to learn more. If you have no

experience, you can answer with something like “Well, I don’t have any commercial

experience in a project, but I have been at organisations that have implemented Agile, and I

am quite interested in learning more about it and how it can help improve the way teams

deliver projects”. This shows both enthusiasm and positivity.

 

How many business cases have you worked on? How were you involved?

A task that business analysts work on occasionally is the preparation of business cases. A

business case is a proposal to an area of the company (usually senior management) about

an idea for a project. It explains what the problem is, what you’d like to do, and what the

benefits are.

A lot of information needs to be gathered to prepare a business case, and often it’s a

business analyst who is brought in to do this work. Sometimes, employers hire business

analysts to prepare business cases for the projects they work on, so they would be asking

about your experience and how many you’ve done. They would also like to know what

your roles were, such as leading the work for a business case, or performing some of

the minor tasks.

 

Tell me about a time you have had trouble working with a stakeholder.

This is another common business analyst interview question for those roles that require

speaking to others to get work done. A business analyst must deal with stakeholders on a

daily basis, and not all of them will be easy to work with.

Stakeholders are those people in the company that are impacted by the project you’re

working on. Many of them are needed for providing input, such as what is needed and how

things should be done. Others just need to find out what’s being done, and others need to

be able to approve what is being done.

From time to time, you’ll come across a stakeholder that may be difficult to work with. They

may be opposed to your project, or they are not being responsive to your calls and emails,

or are unhelpful, or many other reasons. If an employer asks this question, then you should

be ready to provide an answer.

The key to providing an answer to these kinds of questions (those about conflict and

problems) is to choose a small issue and focus on how it was resolved. Don’t

use the opportunity to badmouth previous colleagues. Try to stay positive. Mention a small

issue you had, such as being unable to get in touch with them, or them being unaware of

the project. Mention how you resolved the problem, such as speaking to other people or

asking for decisions to be made, and mention what the outcome was.

 

Tell me about a time you had conflicting requirements from different stakeholders.

This is a common situation in software projects. Some people on the project want certain

functionality, and others don’t want the functionality. Sometimes, a requirement is often

contradicting. For example, one group says the system must do a task this way, and

another group says it needs to do it another way, which conflicts with the first group. It can

be hard to find out the right way or the best way of getting past this.

The employer, similar to the previous question, is trying to find out how you’re able

to handle conflict in your work. Once again, you should mention the problem that

you had, and focus on the positives and how it was resolved.

A common way to get this resolved is to speak to your manager or the project manager. Get

a decision made from higher up in the organisation on how this should be done. Explain to

the interviewer any instances of this happening to you, and remember to focus on the

outcome and how it was resolved.

 

What is the most important skill of a business analyst, in your opinion?This question is asked to see what an interviewee values most about the role. A business

analyst needs to have many skills, and they are asking you what the most important

one is.

With this question, I don’t think there’s a wrong answer. As long as you’re able to mention a

skill that business analysts use, it should be OK. What will really help, though, is that you

mentionwhy you think it’s the most important. If you say communication is the

most important skill, explain why this is the case. The same goes if you mention looking for

gaps in requirements, prioritising work, negotiating with stakeholders, keeping people

informed, writing, or any other skill that is used.

Explaining why you think it is the most important will highlight that you’ve given it some

thought, both for the interview and in your own career.

 

Can you briefly explain what a use case diagram is?

A use case diagram is part of the Unified Modelling Language (UML) and is a popular tool

for business analysts to determine software requirements. The employer is checking both

your knowledge and your ability to explain a concept briefly.

When explaining a use case diagram, you should mention that it is used to show what a

proposed system is supposed to do. Mention that it has actors that represent the people

that interact with it, and use cases which are associated with these users. Mention that it

also accompanies documentation to further explain the use cases.

Remember to keep the explanation brief. It shouldn’t go into detail about extend

relationships and the wording that is used. The employer would like to hear you explain

something briefly so it should be quite short, but enough to get the point across.

 Can you explain what alternative and exception flows are in a use case description?

This is another business analyst interview question that is designed to test your explanation

skills and knowledge of use case modelling. The two concepts they are asking about are

exception flows and alternative flows.

Alternative flows are different paths that can be taken during a user interaction that is

described in a use case. An example of an alternate flow would be for a use case called

“Register New User”, where a user needs to create a registration for the tool. The normal

flow may be to enter details and click Register. An alternative flow would be a valid path

taken in the system that is different to this. Perhaps they click on the Clear Details button.

Perhaps they select “I Already Have an Account”. These would be examples of alternative

flows – they allow a user to take a different path, but they are not errors.

Exception flows are similar to alternative flows, but they are where there is an error or

exception in the process. For example, the required steps need to be detailed when a user

enters invalid data, or if the username is already taken. This is where the exception flow is

discussed.

You should explain what the two concepts are, as well as the difference

between the two. Including some examples would be useful as well.

 What is the difference between a use case and a test case?

Another question you might get is about the difference between a use case and a test case.

This one should be easy to understand, but it can be hard to explain.

A use case represents an activity or process that a user can perform on a system. A test

case indicates how a particular use case is tested to ensure that it operates correctly.

Explain this as best you can to the interviewer. It can be good to include some examples as

well. A use case example could be “Register New User”, as mentioned above. An example

of a test case could be “Enter all numeric values for a new user” or “Enter details for a user

that already exists”. These are designed to test the “Register New User” process.

If you can explain this concept to an interviewer then it should be enough to

demonstrate your knowledge of these terms.

Well, there are some of the most common business analyst interview questions. What other

questions have you heard before? Share them in the comments section below.

5 Tips to Crack an Analytics Interview

Applying for positions in analytics? Interviewers typically look for the following skills for entry

– mid level positions in analytics (3-4 years of experience):

Knowledge of analytical tools like SAS for data processing

A good understanding of statistical concepts and algorithms

For non-fresher positions, recruiters look to see if you have an awareness of issues that you

are likely to face when dealing with business data and business problems.

Here are 5 tips to help you crack an analytics interview, specifically for entry to mid-level

open positions:

1. Allocate most time in your preparation process for reviewing your knowledge of the

analytical tools specified :

Be very proficient with the analytics tool specified: Most often for junior level positions, the

most important criteria in an interview tends to be expertise with an analytical tool (like SAS

or R). The emphasis tends to be around data processing and preparation. Spend time

reviewing concepts of data import and manipulation, especially how to read non-standard

data (mixed data formats, multiple input file types etc), how to join multiple datasets

efficiently, how to conditionally select columns, rows or observations in data, and finally,

how to do heavy duty processing, typically macros or SQL

2. If you have prior experience with analytics or data related processing or analysis, review

the business process end to end as part of your interview preparation:

If you have prior work experience related to analytics or data, interviewers will certainly

spend time asking you to explain the business process and the responsibilities of your

specific role. They are looking for you to have a broad understanding of the end to end

business process, and where your particular role fits in. It is important for you to show that

you understand the source of your data, how it is processed, and how it is ultimately used.

3. Be prepared with at least two business case studies:

Interviewers will want to assess your knowledge of business analytics, not just the tool

proficiency. Spend time reviewing analytics projects you have worked on if you have prior

analytics experience or training. Be prepared to tell them what the business problem was,

what were the data processing steps, what was the algorithm used for creating the models

and why, and how were the model results implemented?  You may be asked about

challenges you faced at any of these stages, so do review issues and challenges in you

past projects and how they were resolved.

 4. Review statistical concepts:

Since analytical algorithms are based on statistical concepts, you will need to be prepared

to answer questions related to fundamental statistical concepts, like hypothesis testing

outcomes and rejection criteria,   model validation measures, and statistical assumptions

that need to hold for implementing different types of algorithms. A quick review of statistical

concepts is a must as part of the interview preparation process.

5. Communicate effectively:

All the preparation in the world is not enough if you do not communicate effectively.

Mentally practice answering mock questions. Focus on questions related to past experience

and business process, with full answers so that you are not thinking too much on the fly at

the actual interview. Of course you cannot anticipate every question, but if you spend time

articulating answers to some questions, you will be better prepared with coherent answers